Table 2.
Multiple linear regression for mobility and environmental predictors.
| Coeff. | SE | t-stat | lower t0.025(213) | upper t0.975(213) | Stand. Coeff. | P | VIF | |
|---|---|---|---|---|---|---|---|---|
| B | 0.804 | 0.0961 | 8.37 | 0.615 | 0.994 | 0 | <0.00001 | |
| Sqrt(Mobility: Indoor recreation) | 0.00385 | 0.000174 | 22.1 | 0.0035 | 0.00419 | 0.842 | <0.00001 | 2.48 |
| Log10(Hay Fever) | −0.132 | 0.0241 | −5.46 | −0.179 | −0.084 | −0.173 | <0.00001 | 1.72 |
| Log10(Solar Radiation) | −0.0637 | 0.0201 | −3.17 | −0.103 | −0.024 | −0.106 | 0.00177 | 1.93 |
| Temperature2 | −0.000561 | 0.0000401 | −14.0 | −0.00063 | −0.000482 | −0.489 | <0.00001 | 2.09 |
Table 2: Overview of outcomes per predictor after multiple linear regression for both mobility and environmental variables. Selection of predictors is based on being (highly) significant and having multicollinearity (VIF) score below 2.5. The function Sqrt returns the square root of the variable.